Method for collection of blood pressure measurement

ABSTRACT

A system to measure blood pressure of a person comprises a software that is configured to obtain two or more sensor information from one or more sensor near simultaneously. The sensor information comprises data points, from which at least one data feature can be derived. Based on the data features derived from the data points, a value of the cardiovascular time delay can be derived. The system can further derive a blood pressure value based on the cardiovascular time delay, and provide the value of the blood pressure, the cardiovascular delay, or other metrics derived from the cardiovascular delay to a user. The sensors can be placed in one or more mobile or wearable devices, which can communicate with each other wirelessly.

This application claims priority to U.S. Provisional Patent ApplicationNo. 61/909,661 filed Nov. 27, 2013, U.S. Provisional Patent ApplicationNo. 61/914,335 filed Dec. 10, 2013, and U.S. Provisional PatentApplication No. 61/948,947 filed Mar. 6, 2014. Where a definition or useof a term in a reference that is incorporated by reference isinconsistent or contrary to the definition of that term provided herein,the definition of that term provided herein is deemed to be controlling.

FIELD OF THE INVENTION

The present invention relates to methods and systems for providing bloodpressure value of a person. In particular, the present invention relatesto methods and systems that can use one or more sensors housed in mobiledevices or wearable devices.

BACKGROUND

The following description includes information that may be useful inunderstanding the present invention. It is not an admission that any ofthe information provided herein is prior art or relevant to thepresently claimed invention, or that any publication specifically orimplicitly referenced is prior art.

In the United States, as of 2014, 78 million American adults, whichcorrespond to about one-third of the American adult population, havehigh blood pressure. However, less than half of those adults with highblood pressure have their condition under control. Another one third ofAmerican adult population has pre-hypertension, in which blood pressurenumbers are higher than normal, but not yet in the high blood pressurerange. High blood pressure costs the nation $47.5 billion each year.This total includes the cost of health care services, medications totreat high blood pressure, and missed days of work. Since 1999, morepeople with high blood pressure, especially those 60 years old or older,have become aware of their condition and gotten treatment.Unfortunately, approximately 1 in 5 U.S. adults with high blood pressurestill do not know that they have the condition.

Both invasive methods and noninvasive methods have been used to measurepatients' blood pressure. Sphygmomanometer is one of the commonly usednoninvasive devices to measure blood pressures. To begin blood pressuremeasurement, a user should use a properly sized blood pressure cuff. Thecuff is wrapped around the upper arm of the person in a comfortableposition. The blood pressure of the person is measured during the periodthat the cuff is rapidly inflated and deflated, while a healthcareprovider listens to the sound of knocking for the person's systolicpressure with the stethoscope and simultaneously observes thesphygmomanometer. However, because of its size and complicated method ofuse, measuring blood pressure with sphygmomanometers may not be aconvenient method for people who desire to measure blood pressure duringwork, exercise, or travel.

Many efforts have been put forth to make a method of the blood pressuremeasurement more convenient and user friendly. For example, U.S. PatentApplication No. 2013/0072145 to Dantu discloses a method fordifferential estimation of blood pressure using two mobile phones. Inthis method, one mobile phone is used to record heart sound, and theother mobile phone is used to record video data from the finger-tip ofthe subject. Signals recorded from two different mobile phones aresynchronized by a synchronization protocol, such as Master-Slavearchitecture or master time stamp. However, this method onlycontemplates a combination of sound and visual signals and absolutelyrequires the use of two separate mobile phones.

In another example, U.S. Patent Application No. 2005/0228299 to Banetdiscloses a method of monitoring vital signs of patient over a wirelessnetwork. In Banet, the monitoring device comprises an adhesive patchsensor that makes a trans-dermal, optical measurement of thetime-dependent dynamics of blood flowing in an underlying artery.However, Banet's method also fails to contemplate the use of other typesof sensors to measure blood pressure of the patient and requires thecompression of the person's artery to restrict blood flow. Allpublications identified herein are incorporated by reference to the sameextent as if each individual publication or patent application werespecifically and individually indicated to be incorporated by reference.

Thus, there is still a need for an improved method to measure bloodpressure noninvasively using various sensors, which is easy to use andprovides accurate blood pressure data to a user.

SUMMARY OF THE INVENTION

The inventive subject matter provides systems and methods for measuringblood pressure of a person. One aspect of the invention is the method tomeasuring a person's blood pressure. The method comprises a step ofproviding a software configured to obtain a first sensor informationfrom a first sensor and a second sensor information from a second sensornear simultaneously. The first sensor information comprises a first datapoint, and the second sensor information comprises a second data point.The method further comprises a step of deriving a first data featurebased on the first data point and a second data feature based on thesecond data point. Based on the first data feature and the second datafeature, a time delay value can be derived, which is correlated to ablood pressure value of the person. Based on the correlation between thetime delay and the blood pressure, the blood pressure value of theperson is derived and provided to a user.

Other aspects of the invention includes a system of measuring bloodpressure of a person. The system includes sensors: a first sensorproviding a first sensor information, and a second sensor providing asecond sensor information. The system further comprises a computersystem with a processor, which is configured to execute a softwarestored on a non-transient computer-readable memory. The software canactivate the first sensor and the second sensor, and synchronize thefirst and second sensor information by obtaining the first and secondsensor information near simultaneously. The first sensor informationcomprises a first data point, and the second sensor informationcomprises a second data point. The software is further configured toderive a first data feature based on the first data point and a seconddata feature based on the second data point. Based on the first datafeature and the second data feature, the software is configured toderive a time delay, which is correlated to a blood pressure value ofthe person. Then, the software can derive a blood pressure value of theperson based on the time delay.

Another aspect of the invention includes a method of measuring acardiovascular time delay of a person. The method comprises a step ofproviding a software, which is configured to obtain a first sensorinformation from a first sensor, and a second sensor information from asecond sensor near simultaneously. The first sensor informationcomprises a first data point, and the second sensor informationcomprises a second data point. The software is further configured toderive a first data feature based on the first data point and a seconddata feature based on the second data point. Then, based on the firstdata feature and the second data feature, a cardiovascular time delaycan be derived. The method further comprises a step of providing a userthe cardiovascular time delay value or a metric derived from thecardiovascular time delay of the person.

Another aspect of the invention includes a system which measures acardiovascular time delay of a person. The system includes a firstsensor providing a first sensor information, and a second sensorproviding a second sensor information. The system further comprises acomputer system with a processor, which is configured to execute asoftware stored on a non-transient computer-readable memory. Thesoftware can activate the first sensor and the second sensor, andsynchronize the first and second sensor information by obtaining thefirst and second sensor information near simultaneously. The firstsensor information comprises a first data point, and the second sensorinformation comprises a second data point. The software is furtherconfigured to derive a first data feature based on the first data pointand a second data feature based on the second data point. Based on thefirst data feature and the second data feature, the software isconfigured to derive a cardiovascular time delay of the person. Then,the software can provide a user the cardiovascular time delay value or ametric derived from the cardiovascular time delay of the person.

Another aspect of the invention includes a method of measuring a bloodpressure of a person using at least three sensors. This method comprisesa step of providing a software, which is configured to obtain a firstsensor information from a first sensor, a second sensor information froma second sensor, and a third sensor information from a third sensor nearsimultaneously. The first sensor information comprises a first datapoint, the second sensor information comprises a second data point, andthe third sensor information comprises a third data point. The softwareis further configured to derive a first data feature based on the firstdata point, a second data feature based on the second data point, and athird data feature based on the third data point. Then, the software isconfigured to derive a first time delay based on the first data featureand the second data feature, a second time delay based on the first datafeature and the third data feature, and a third time delay based on thesecond data feature and the third data feature. Among three time delaysobtained based on the first, second, and third data features, at leasttwo of the first, second, and third time delays are correlated to ablood pressure value of the person. Based on the correlations among thefirst, second and third time delays and the blood pressure, the softwareis configured to derive a blood pressure value of the person. The methodfurther comprises a step of providing a user the blood pressure value ofthe person.

Another aspect of the invention includes a method of measuring bloodpressure of a person by making a skin acoustic duct seal. In thismethod, a user is instructed to contact an opening of an acoustic ductof a device with the person's chest to create a skin acoustic duct seal.The method further comprises a step of providing a software, which isconfigured to obtain a first sensor information from a first sensor,wherein the first sensor information is an acoustic informationtransmitted via the acoustic duct and the acoustic information comprisesa first data point, and a second sensor information from a secondsensor. The second sensor information comprises a second data pointobtained near simultaneously with the first sensor information, andsecond sensor information comprises a second data point. The software isfurther configured to derive a first data feature based on the firstdata point, and the second data feature based on the second data point.Based on the first and second data features, a time delay can bederived, which is correlated with the blood pressure of the person.Then, the blood pressure value can be derived based on the time delay.The method further comprises as step of providing a user the bloodpressure value of the person.

Another aspect of the invention includes a method of measuring acardiovascular time delay of a person by making a skin acoustic ductseal. In this method, a user is instructed to contact an opening of anacoustic duct of a device with the person's chest to create a skinacoustic duct seal. The method further comprises a step of providing asoftware, which is configured to obtain a first sensor information froma first sensor, wherein the first sensor information is an acousticinformation transmitted via the acoustic duct and the acousticinformation comprises a first data point, and a second sensorinformation from a second sensor. The second sensor informationcomprises a second data point obtained near simultaneously with thefirst sensor information, and second sensor information comprises asecond data point. The software is further configured to derive a firstdata feature based on the first data point, and the second data featurebased on the second data point. Based on the first and second datafeatures, a cardiovascular time delay can be derived. The method furthercomprises as step of providing a user the cardiovascular time value or ametric derived from the cardiovascular time delay of the person. Thismetric includes blood pressure.

Another aspect of the invention includes a method of measuring bloodpressure of a person by using two visual sensors. In this method, a useris instructed to point a first photodetector of a device at a portion ofthe person's body. The method further comprises a step of providing asoftware, which is configured to obtain a first sensor information froma first sensor and a second sensor information from a second sensor nearsimultaneously with the first sensor information. The first and secondsensors comprise the first and second photodetectors. The first sensorinformation comprises a first data point, and the second sensorinformation comprises a second data point. The software is furtherconfigured to derive a first data feature based on the first data pointand a second data feature based on the second data point. Based on thefirst data feature and the second data feature, the software can derivea time delay, which is correlated to a blood pressure value of theperson. Then the software can derive a blood pressure value of theperson based on the time delay. The method further comprises a step ofproviding a user the blood pressure value of the person.

Various objects, features, aspects and advantages of the inventivesubject matter will become more apparent from the following detaileddescription of preferred embodiments, along with the accompanyingdrawing figures in which like numerals represent like components.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates diagrams of three different sensor signals for aheartbeat.

FIG. 2 illustrates a diagram of synchronous retrieval of the latestsensor values from asynchronously updating sensors.

FIG. 3 illustrates a diagram of synchronous retrieval of latest sensorvalues and system clock time stamps.

FIGS. 4A-C illustrate one exemplary embodiment of blood pressuremeasurement by making a skin acoustic duct seal and recordingphonocardiograms. FIG. 4A illustrates a perspective view of the producthousing for a mobile computational device. FIG. 4B illustrates a sideview of the product housing for the mobile computational device. FIG. 4Cillustrates a schematic view of measuring acoustic heart activity on theperson's chest.

FIGS. 5A-B illustrate one exemplary embodiment of blood pressuremeasurement by using a mobile computational device to record aballistocardiogram and a plethysmogram. FIG. 5A illustrates a schematicview to measure blood pressures using ballistocardiogram and aplethysmogram signals. FIG. 5B illustrates a schematic diagram toprocess ballistocardiogram and a plethysmogram signals.

FIGS. 6A-B illustrate one exemplary embodiment of blood pressuremeasurement by using a mobile computational device to record twoplethysmograms. FIG. 6A illustrates a schematic view to measure bloodpressures using two plethysmograms. FIG. 6B illustrates a schematicdiagram to process two PPG signals.

FIGS. 7A-B illustrate one exemplary embodiment of blood pressuremeasurement by using a patch and a wearable device to record twoplethysmograms at different locations of the body. FIG. 7A illustrates aschematic view to measure blood pressure using two plethysmograms. FIG.7B illustrates a schematic diagram to process two PPG signals.

FIGS. 8A-C illustrate one exemplary embodiment of blood pressuremeasurement by using a mobile computational device and a patch to recorda plethysmogram and an electrocardiogram. FIG. 8A illustrates aschematic view to measure blood pressure using a mobile computationaldevice. FIG. 8B illustrates a schematic view to measure blood pressureusing a patch. FIG. 8C illustrates a schematic diagram to process ECGsignal and PPG signal.

FIGS. 9A-B illustrate one exemplary embodiment of blood pressuremeasurement by using a patch and a wearable device to record anelectrocardiogram and a plethysmogram. FIG. 9A illustrates a schematicview to measure blood pressure using two wearable devices. FIG. 9Billustrates schematic diagrams to process ECG signal and PPG signal.

FIGS. 10A-B illustrate one exemplary embodiment of blood pressuremeasurement by using a wearable device to record an electrocardiogramand a plethysmogram. FIG. 10A illustrates a schematic view to measureblood pressure using one wearable device. FIG. 10B illustrates schematicdiagrams to process ECG signal and PPG signal.

FIGS. 11A-B illustrate one exemplary embodiment of blood pressuremeasurement by using a wearable device to record a plethysmogram and aballistocardiogram. FIG. 11A illustrates a schematic view to measureblood pressure using one wearable device. FIG. 11B illustrates aschematic diagram to process BCG signals and PPG signals.

FIGS. 12A-B illustrate one exemplary embodiment of blood pressuremeasurement by using a mobile computational device to record anelectrocardiogram and a plethysmogram. FIG. 12A illustrates a schematicview to measure blood pressure using one mobile device. FIG. 12Billustrates a schematic diagram to process ECG signal and PPG signal.

DETAILED DESCRIPTION

The present invention relates to methods and system for measuring andproviding blood pressure of a person. The principles and operations forsuch methods and systems, according to the present invention, may bebetter understood with reference to the accompanying description anddrawings.

It should be noted that any language directed to a computer should beread to include any suitable combination of computing devices, includingservers, interfaces, systems, databases, agents, peers, engines,modules, controllers, or other types of computing devices operatingindividually or collectively. One should appreciate that computingdevices comprise a processor configured to execute software instructionsstored on a tangible, non-transitory computer readable storage medium(e.g., hard drive, solid state drive, RAM, flash, ROM, etc.). Thesoftware instructions preferably configure the computing device toprovide the roles, responsibilities, or other functionality as discussedbelow with respect to the disclosed apparatus. In especially preferredembodiments, the various servers, systems, databases, or interfacesexchange data using standardized protocols or algorithms, possibly basedon HTTP, HTTPS, AES, public-private key exchanges, web service APIs,known financial transaction protocols, or other electronic informationexchanging methods. Data exchanges preferably are conducted over apacket-switched network, the Internet, LAN, WAN, VPN, or other type ofpacket switched network.

The following discussion provides many example embodiments of theinventive subject matter. Although each embodiment represents a singlecombination of inventive elements, the inventive subject matter isconsidered to include all possible combinations of the disclosedelements. Thus if one embodiment comprises elements A, B, and C, and asecond embodiment comprises elements B and D, then the inventive subjectmatter is also considered to include other remaining combinations of A,B, C, or D, even if not explicitly disclosed.

As used herein, and unless the context dictates otherwise, the term“coupled to” is intended to include both direct coupling (in which twoelements that are coupled to each other contact each other) and indirectcoupling (in which at least one additional element is located betweenthe two elements). Therefore, the terms “coupled to” and “coupled with”are used synonymously.

In some embodiments, the numbers expressing quantities or ranges, usedto describe and claim certain embodiments of the invention are to beunderstood as being modified in some instances by the term “about.”Accordingly, in some embodiments, the numerical parameters set forth inthe written description and attached claims are approximations that canvary depending upon the desired properties sought to be obtained by aparticular embodiment. In some embodiments, the numerical parametersshould be construed in light of the number of reported significantdigits and by applying ordinary rounding techniques. Notwithstandingthat the numerical ranges and parameters setting forth the broad scopeof some embodiments of the invention are approximations, the numericalvalues set forth in the specific examples are reported as precisely aspracticable. The numerical values presented in some embodiments of theinvention may contain certain errors necessarily resulting from thestandard deviation found in their respective testing measurements.Unless the context dictates the contrary, all ranges set forth hereinshould be interpreted as being inclusive of their endpoints andopen-ended ranges should be interpreted to include only commerciallypractical values. Similarly, all lists of values should be considered asinclusive of intermediate values unless the context indicates thecontrary.

As used in the description herein and throughout the claims that follow,the meaning of “a,” “an,” and “the” includes plural reference unless thecontext clearly dictates otherwise. Also, as used in the descriptionherein, the meaning of “in” includes “in” and “on” unless the contextclearly dictates otherwise.

All methods described herein can be performed in any suitable orderunless otherwise indicated herein or otherwise clearly contradicted bycontext. The use of any and all examples, or exemplary language (e.g.,“such as”) provided with respect to certain embodiments herein isintended merely to better illuminate the invention and does not pose alimitation on the scope of the invention otherwise claimed. No languagein the specification should be construed as indicating any non-claimedelement essential to the practice of the invention.

Groupings of alternative elements or embodiments of the inventiondisclosed herein are not to be construed as limitations. Each groupmember can be referred to and claimed individually or in any combinationwith other members of the group or other elements found herein. One ormore members of a group can be included in, or deleted from, a group forreasons of convenience and/or patentability. When any such inclusion ordeletion occurs, the specification is herein deemed to contain the groupas modified thus fulfilling the written description of all Markushgroups used in the appended claims.

One aspect of the present invention includes a method of measuring bloodpressure of a person using one or more devices operated by one or moresoftware. The software is configured to obtain sensor information from asensor. In a preferred embodiment, a sensor is a hardware sensor on amobile device (e.g., a cell phone, a smart phone, a handheld computer,an iPAD®, and a PDA, etc.). In some embodiments, it is contemplated thata sensor is a hardware sensor on a wearable device (e.g., a chest strap,a watch, an eyeglasses, a headphone, a hat, a helmet, a glove, anarmband, a headband, a headset, a wristband, an ankle band, a cloth, aring, and a toe cap, etc.), or a patch (e.g., a partially disposablepatch, a wholly disposable patch, a non-disposable patch, a fabricpatch, a plastic patch, and a metal patch, etc.).

It is generally preferred that the mobile device, the wearable device,or the patch comprises an embedded electrical system, a power source,and a product housing. The embedded system further comprises anelectrical hardware circuit consisting of a digital controller, ananalog-to-digital converter, a non-transient computer-readable memory(e.g., a hard drive, a flash drive, RAM, etc.). The non-transientcomputer-readable memory stores a software, which is uploaded to atleast one or more processing units (e.g., processors, processing cores,digital controllers, etc.). The software is responsible for drivinghardware components to accomplish the defined tasks (e.g., controllingsensor functionality, capturing sensor signals, activating sensors,etc.).

Many types of sensors embedded in or coupled with the mobile device, thewearable device, or the patch, can be used to obtain sensor information.In a preferred embodiment, sensors may include an acoustic-to-electricaltransducer (e.g., microphone), an accelerometer, an array of electrodeshaving at least two electrodes, a photodetector (e.g., a light sensor,an image sensor, a semiconductor charge-coupled device (CCD), an activepixel sensor in complementary metal-oxide-semiconductor (CMOS), a N-typemetal-oxide-semiconductor (NMOS, live MOS), etc.). However, it is alsocontemplated that other types of sensors can be used to obtain sensorinformation. For example, sensors may include a chemical sensor, amagnetic sensor, a moisture sensor, a pressure sensor, a thermal sensor,a presence sensor, and any other types of sensors suitable for obtaininginformation related to blood pressure.

Each type of sensor may provide different type of sensor information inrelation to a person's blood pressure. For example, anacoustic-to-electrical transducer embedded in, or placed at the mobiledevice, the wearable device, or the patch, can provide sensorinformation of the acoustic heart activity in a form of phonocardiogram(PCG). The turbulent closure of heart valves cause acousticperturbations that can be detected with a proper acoustic transducer(e.g., stethoscope). The acoustic heart activity trace captured by theacoustic-to-electrical transducer contains physiological informationabout the occurrence of the closure of the atrioventricular andsemilunar valves of the person's heart as well as physiologicalinformation about the timing related to the ejection of blood from theleft ventricle of the heart into the aorta and peripheral arterial tree.

To record a PCG signal, the software activates theacoustic-to-electrical transducer. Incident, analog acoustic waves ofthe acoustic heart activity induce fluctuations in outputted electricalactivity of the acoustic-to-electrical transducer. This electricaloutput is digitized via a dedicated analog-to-digital convertercomponent, an analog-to-digital converter equipped digital controllercomponent, or any hardware component within the embedded electricalsystem equipped with the ability to convert an analog electrical signalinto a discretely sampled digital signal.

A PCG signal can be generally represented as a waveform. Each waveformis associated with a single cardiac cycle. Signal peak detection andcommon bandpass signal processing techniques are used to isolate thefrequencies of interest in the acoustic heart activity trace signal,particularly those below 1000 Hz, and used to identify the precise timereference associated with left ventricular contraction and bloodejection from the heart into the aorta for a single cardiac cycle.

In a preferred embodiment, the device includes an accelerometer torecord mechanical heart activity. The mechanical heart activity tracecaptured by the accelerometer contains physiological information aboutthe mechanical, cardiac contraction event, generally represented as aform of the ballistocardiogram (BCG). A single cardiac cycle involvesthe mechanical contraction of the ventricles which generate the largestmechanical force during a single cardiac cycle. The BCG is a measure ofthe mechanical forces generated by mechanical activities of the heart,which include the transient contraction of cardiac muscle and ejectionrecoil forces of the blood being ejected from the ventricles into theaorta and pulmonary artery. The mechanical force waves can be passedthrough the body tissue and can be strongly detected in the area closestto the heart and are also detectable at the head and ear. A preferable,but by no means only, way to place an accelerometer for left ventricularcontraction force detection is by coupling the product housing with thechest of the person closest to the apex of the heart, where the heart isclosest to the skin and where the left ventricle is located. Propersignals can be acquired elsewhere on the chest of the person or at otherlocations on the surface of the body where proper mechanical coupling ofproduct housing can be achieved.

In a preferred embodiment, a mobile computational device contains anembedded system that includes an electrical circuit comprising aMEMS-based accelerometer. The electrical circuit is fastened ormechanically fixed to the product housing of the mobile computationaldevice such that a force vector applied to the product housing isequally applied to the accelerometer. A software uploaded to the digitalcontroller of the embedded system handles the accelerometer sensorupdates and is provided with at least the X, Y, Z components ofacceleration from the accelerometer. The component of acceleration(either the X, Y, or Z component) that is relatively orthogonal to thechest plane where contact with the mobile computational device is madeis used for data capture and the remaining other two signal componentsmay or may not be used for data capture. The selection for thecomponents of acceleration may be dependent on the configuration of theaccelerometer, the relative orientation of the accelerometer to theproduct housing, and the relative position of the product housing to thechest plane of the person when the product housing is in contact withthe person's chest.

Middle waveform shown in FIG. 1 shows an example of the BCG waveform. ABGC waveform is almost entirely a result of ventricular mechanicalactivity of the heart when it is properly measured at the appropriatelocation on the chest or other body surface (e.g., head or ear) with anaccelerometer equipped mobile computational device with sufficientmechanical coupling between the chest (or body surface) and the device.For example, the values of the J-K “max” negative slope or a J amplitudethreshold are dependent on the ventricular mechanical activity of theheart. In addition, the amplitude of the J peak is proportional to theforce of ventricular contraction. The HL interval correlates well withthe total time of ventricular ejection, which represents the total timethat blood is being ejected into the aorta. Furthermore, the onset of Hrepresents the beginning of the blood ejection from the ventricles andthe commencement of L represents the end of blood ejection from theventricles. Thus, the amplitude of the peak of the component ofacceleration selected for each ventricular cardiac contraction event isproportional to the contractile force of the heart and stroke volume. Acomponent of acceleration (e.g., a peak acceleration, a max positivechange in acceleration, a max negative change in acceleration, etc.)selected for each ventricular cardiac contraction event is selected andthe time at which it occurs serves as the time reference for the leftventricular contraction event or time of blood ejection from the heart.

In some embodiment, an array of electrodes can be used to obtain sensorinformation of relevant to a person's blood pressure. An array ofelectrodes embedded in, or placed on the mobile device, the wearabledevice, or the patch, can provide sensor information of electrical heartactivity in a form of electrocardiogram (ECG). The electrical heartactivity trace contains physiological information about the occurrenceof the electrical polarization and depolarization of cardiac tissue.

Upper waveform shown in FIG. 1 shows an example of the ECG waveform. Theelectrical activity of the heart can be detected with a pair ofelectrodes placed in contact with the surface (e.g., skin, etc.) of thebody. Improved electrical heart activity detection is achieved withelectrode placement wherein each electrode is placed on the surface(e.g., skin, etc.) of the body such that the electrical potential paththrough the body between the electrode pair crosses the path of theheart. Signal peak detection, represented as the peak of the waveform,R, can be used to identify a precise time reference associated withelectrical systole and subsequent left ventricular mechanicalcontraction of the heart.

In some embodiments, a photodetector can be used to obtain sensorinformation relevant to a person's blood pressure. A photodetectorembedded in, or placed at the mobile device, the wearable device, or thepatch, can provide sensor information in a form of photoplethysmogram(PPG). The software activates the photodetector and an incident lightsource (e.g., camera flash, etc.), if available. Ambient light may beused in place of an incident light source in some embodiments. Thephotodetector and incident light source, if included, are either indirect contact with the skin of a regional tissue of interest or aimedat the skin of a regional tissue of interest.

Human blood contains intrinsic biophysical properties in which itabsorbs incident light photons. With each cardiac contraction, anarterial pressure wave is generated and propagated along the arterialtree to the periphery of the cardiovascular system, reaching themicrovasculature of the subcutaneous and dermal tissue of the skin.Thus, periodic cardiac contractions lead to localized increases to bloodvolume at the person's regional tissue of interest; for example, thepalmar tissue bed of the digit, in contact with the photodetector. Theselocalized increases to blood volume cause more light to be absorbed andless light to be reflected back to the photodetector. Because largervolumes of blood absorb greater amounts of incident light photons,changes in subcutaneous and dermal tissue blood volume can be detectedwith a photodetector aimed at or in direct contact with the subcutaneousand dermal tissue bed of interest. Thus, the photoplethysmogramrepresents the local tissue blood volume activity trace, which containsphysiological information about the pulsatile fluctuations of bloodvolume present in the micro-vasculature and capillary beds of a regionof tissue near the surface of the body.

Incident, analog fluctuations in reflected light from the regionaltissue of interest; for example, the palmar tissue bed of the person'sdigit, in contact with or aimed at the photodetector induce either 1)fluctuations in outputted electrical activity of the photodetector,which is subsequently digitized via a dedicated analog-to-digitalconverter component, an analog-to-digital converter equipped digitalcontroller component, or any hardware component within the embeddedelectrical system equipped with an analog to digital converter) or 2)fluctuations in the individual color components (e.g., RGB components)of pixels from an image sensor type photodetector.

The local tissue blood volume activity in a form of PPG can be capturedon a tissue area on a person's body for contact with the photodetector.The point of contact can be any other location on the surface of thebody at a sufficient cardiovascular distance from the heart or asufficient difference in cardiovascular distance from the heart fromanother photodetector. Signal strength (e.g., pulsatile blood volumesignals) is stronger near the termination of the arterial tree such asnear the fingers and toes.

Bottom waveform shown in FIG. 1 shows an example of a PPG or IPG signalas a waveform. Each waveform is associated with the arrival of anarterial pressure wave generated from a single cardiac cycle, which isrepresented by a single left ventricular contraction of the heart. Eachwaveform has a foot of the waveform W, a point of maximum slope of thewaveform W-Y, and a peak of the waveform Y.

In some embodiments, local tissue blood volume signals can be detectedusing an array of electrodes. Impedance plethysmography (IPG), which mayalso be referred to as electrical plethysmography, electrical impedanceplethysmography, or bioimpedance plethysmography, is a non-invasivemethod for capturing localized blood volume changes in a regional tissueof interest. In practice, it usually involves placing electrodes indirect skin contact at the tissue region of interest and measuringchanges in electrical potential of the tissue while driving a smallcurrent of electricity through the tissue. Blood is an ionic conductor,which permits the flow of electrical current in one or more directions.Thus, electrical current can flow better through blood than othertissues of the body. Therefore, the more the blood there is in a tissuesegment, the greater the conductivity of that tissue segment, and thelesser the impedance of that tissue segment. IPG can be used to detectarterial blood pulse waves. With each propagating pulse wave through anartery in a given tissue segment, there is a transient increase in bloodvolume in that tissue segment that causes a transient change in theimpedance of that tissue segment, which is measured using the sensingelectrodes of the IPG sensor.

To capture an IPG signal, an array of current electrodes or drivingelectrodes are placed in direct contact with the skin of the tissueregion of the person and are used to drive a low-amplitude AC current.An AC electrical current is used usually within the frequency range of20-100 kHz through the said tissue region of the person. An array ofmeasurement electrodes, sometimes referred to as sensing electrodes orvoltage electrodes, are also placed in direct contact with the skin ofthe tissue region of the person, usually between the current electrodes,and are used to measure the frequency-dependent AC potential through theregional tissue of the person.

It is preferred that the array of current electrodes is in a differentarray of electrodes as the measurement electrodes. In some embodiments,either 2 or 4 total electrodes can be used in the hardware configurationof an IPG sensor. If the array of current electrodes is the same as thearray of measurement electrodes and there are 2 electrodes in total,then the hardware configuration is a 2-electrode or bipolarconfiguration. If the array of current electrodes is different than thearray of measurement electrodes and there are 4 electrodes in total thenthe hardware configuration is a 4-electrode or tetrapolar configuration.

It is preferred that a single waveform in the sensor informationcorresponds to a single data point of the sensor information. However,it is also contemplated that a single waveform corresponds to more thantwo data points. Further, it is also contemplated that more than twowaveforms correspond to a single data point.

In some embodiments, the sensor information comprises more than one datapoint. For example, PPG, PCG, or BCG can be recorded during a period ofmultiple cardiac cycles, which is represented as multiple waveforms.Generally, only one data point from each sensor is required to derivethe blood pressure value of the person. However, in some embodiments, itis contemplated that more than one data points are used from one sensoris used to derive the blood pressure value of the person.

Each data point in the sensor information can be represented by one ormore features of the waveform. Some features of the waveform include apeak of the waveform, a foot of the waveform, a point of maximum slopeof the waveform, a point of minimum slope of the waveform, a time topeak of the waveform, a width of the peak, a peak of the first or secondderivative of the waveform, a foot of the first or second derivative ofthe waveform, a point of maximum slope of the first or second derivativeof the waveform, and a point of minimum slope of the first or secondderivative of the waveform. Any other features of the waveform that canbe derived from the waveform by an ordinary person in the art are alsocontemplated to be used to represent the data point.

When more than one sensor information for a single cardiac cycle isdetected or recorded by one or more types of sensors, a correlationbetween two or more sensor information can provide more detailedinformation for a more accurate measurement of the blood pressure. FIG.1 shows examples of time delays 105, 110, 115. For example, the timedifference 105 between the onset of R of the ECG to the onset of W ofthe PPG or IPG represents a time delay or pulse arrival time thatcorrelates to a systolic pressure. However, the pulse arrival time doesnot correlate as significantly with a diastolic pressure because itincludes a time delay known as the pre-ejection period, which is thetime delay from electrical to mechanical systole of the heart during asingle cardiac cycle. The addition of the BCG to the ECG and PPG or IPGenables the capture of the time difference 115 between the peakamplitude R of ECG to the max positive slope I-J of BCG, whichcorrelates with a pre-ejection period. Furthermore, the time difference110, or pulse transit time, between the max positive slope I-J of BCGand onset of W of the PPG correlates with a diastolic pressure.

When two or more sensor information is obtained and used for derivingblood pressure value, it is preferred that those sensor information aresynchronized together so that the data points from those sensorinformation correspond to the same cardiac cycle. It is contemplatedthat there are two methods to synchronously capture sensor data: 1)using an embedded system design that enables the synchronous retrievalof the latest sensor values from asynchronously updating sensors, and 2)using an embedded system design that enables the synchronous retrievalof the latest sensor values and system clock time stamps. The finaloutput of both methods is the session time-synchronized signal traces,which can be passed on for further processing. Note that the “buffer”used herein refers to a “data buffer” which refers a region of physicalmemory storage used to temporarily store data.

The first method to synchronously capture sensor data is described inFIG. 2. In this method, asynchronously updating sensor data can be nearsimultaneously captured. This method of synchronization is useful tomeasure blood pressure using a single mobile computational device. Thesoftware running on the digital controller of the embedded system of themobile computational device, initiates a measurement session of whichinitiation is triggered by user interaction with the mobilecomputational device. Periodic sampling of digitized sample A (e.g., aplethysmogram) using sensor A (e.g., a photodetector) is conducted at afrequency m, and another periodic sampling of digitized sample B (e.g.,phonocardiogram information) using sensor B (e.g., anacoustic-to-electrical transducer) is conducted at a different frequencyn. Thus, digitized sample A and sample B are updated asynchronously.

The software allocates memory space within the embedded system, eitheron a memory-equipped digital controller component or dedicated memorycomponent, to hold in memory slots for: 1) the most recent digital valueof the acoustic-to-electrical transducer (memory location X), 2) themost recent digital value of the photodetector (memory location Y), and3) the session signal trace buffer.

It is preferred that the digitized sample A and sample B are constantlyupdated. The latest update of the digitized sample B, for example,outputs of the acoustic-to-electrical transducer, which is the latestacoustic digital value, is routed into and handled by the software wherea specific thread or loop of code is responsible for receiving thelatest acoustic digital values. The latest update of the digitizedsample A, for example, outputs of the photodetector, either in the formof frames comprised of pixels each pixel of which is comprised of anred, green, and blue component for an image-type photodetector orsingle-value intensity values, the latest photodetector digital value,is also routed into and handled by the software where a specific threador loop of code is responsible for receiving the latest photodetectordigital values.

Every time the latest acoustic digital value is routed into and handledby the software, it is stored in memory as the most recent digital valueof the acoustic-to-electrical transducer. Similarly, every time thelatest photodetector digital value is routed into and handled by thesoftware, it is stored in memory as the most recent digital value of thephotodetector.

In a synchronous periodic fashion, the software runs another thread orloop of code that is responsible for retrieving the most recent digitalvalue of the acoustic-to-electrical transducer stored in memory and themost recent digital value of the photodetector stored in memory. At thesame time, the software generates a time stamp, as precise as possible,but ideally precise to less than or equal to one millisecond. However itis contemplated that the time stamp can be generated at an interval ofless than 1 millisecond, less than 5 milliseconds, less than 10milliseconds, less than 50 milliseconds, or less than 100 milliseconds.The latest digitized sample from sensor A, sensor B, and system clocktimestamp at time t are appended to the session signal trace buffer inmemory, generating a synchronized set of parallel physiological signaltraces.

The second method to synchronously capture sensor data is described inFIG. 3. In this method, periodic sampling digitized sample A (e.g.,plethysmogram) using sensor A (e.g., a photodetector) and anotherdigitized sample B (e.g., phonocardiogram information) using sensor B(e.g., an acoustic-to-electrical transducer). The most recent digitalvalue of the sample A and sample B are near simultaneously captured. Asthe frequency of capturing the digital value of the sample A and sampleB is much shorter than the frequency of the cardiac cycle (e.g., lessthan 1 millisecond, less than 5 millisecond, less than 10 millisecond,less than 50 millisecond, less than 100 millisecond, etc.), nearsimultaneously captured the digital value of the sample A and sample Bare likely to correspond to the same cardiac cycle (e.g., a singleheartbeat).

In a synchronous periodic fashion, the software runs another thread orloop of code that is responsible for retrieving the most recent digitalvalue of the acoustic-to-electrical transducer stored in memory and themost recent digital value of the photodetector stored in memory. At thesame time, the software generates a time stamp, as precise as possible,but ideally precise to one millisecond. However it is contemplated thatthe time stamp can be generated at an interval of less than 1millisecond, less than 5 milliseconds, less than 10 milliseconds, lessthan 50 milliseconds, or less than 100 milliseconds. The latestdigitized sample from sensor A, sensor B, and system clock timestamp attime t are appended to the session signal trace buffer in memory,generating a synchronized set of parallel physiological signal traces.

In some embodiments, it is also contemplated that a synchronizationmethod using a time stamp can be used to synchronize asynchronouslycaptured digital value of the sample. In this method, all changes to theasynchronously captured digital values are marked with time stamps.Synchronization proceeds by transferring all asynchronously captureddigital values with a time stamp later than the previoussynchronization.

In addition, it is also contemplated that the synchronization of sensorinformation can be conducted via synchronizing the time stamp betweentwo devices. One of the methods contemplated herein is the periodicinaudible, high frequency sound synchronization method. This method canbe used between two wireless devices. In this method, the first devicecontains a speaker and the second device contains a microphone. Asynchronization process between the two devices is initiated. Thesynchronization process occurs at the beginning of each measurementsession or at a sufficient interval to maintain a desired level ofsynchronicity between the two devices to avoid an undesirable level ofclock drift. An inaudible high frequency sound pulse of a pre-determinedfrequency (e.g., 21 kHz) is emitted by the speaker of the first device.Simultaneous with the moment of emission of the sound pulse from thefirst device, the first device creates and stores a first time stamp ona memory location within the embedded system of the first device. Thesecond device is programmed to look at a pre-determined frequency bandthat matches the pre-determined frequency of the sound pulse emitted bythe speaker of the first device. Through the use of a continuousdiscrete Fourier transform (e.g., a fast Fourier transform) applied tothe real-time stream of microphone sensor information from themicrophone on the second device, the second device detects the precisemoment of the amplitude of a pre-determined frequency band (e.g., anarrow band around 21 kHz) that reaches a pre-defined threshold.Simultaneous with the precise moment that the second device detects theprecise moment the amplitude of a pre-determined frequency band (e.g., anarrow band around 21 kHz) that reaches a pre-defined threshold, thesecond device creates and stores a second time stamp on a memorylocation within the embedded system of the second device. At a latertime, when the sensor information is wirelessly moved from the seconddevice to the first device, the second time stamp is also moved onto thefirst device. A time delay is calculated between the first time stampand the second time stamp is calculated. Whether the time delay ispositive or negative, it is used to adjust the time-alignment of sensorinformation that is collected from both the first device and seconddevice. It is important to note that a wide range of varying frequenciescan be selected in the human inaudible range.

Another method of synchronizing the time stamp between two devices isthe continuous inaudible, high frequency sound synchronization method.This method can be used between two wireless devices. In this method,the first device contains a microphone and the second device contains aspeaker. A measurement session involving the two devices is initiated.The initiation process of the first device encompasses the first deviceactivating the microphone. The first device also initiates recordingsensor information from a sensor within the first device to a memorylocation within the embedded system of the first device. The seconddevice activates a speaker and a sensor within the second device. Thesecond device is programmed to emit high frequency sounds through itsspeaker within a human-inaudible frequency band (e.g., a finite numberof frequencies within a range of 20-22 kHz). The frequency of soundemitted by the speaker on the second device at any time (t=x) isdirectly proportional to the value of the sensor information from thesensor on the second device at the same time (t=x). More specifically, apre-determined number of numerical values are selected and mapped to apre-determined finite number of frequency bands (e.g., a finite numberof bands within a range of 20-22 kHz). The microphone of the firstdevice captures the sound emitted by the speaker of the second devicewith a negligible delay caused by to the speed of sound travel. Throughthe use of a continuous discrete Fourier transform (e.g., a fast Fouriertransform) applied to the real-time stream of microphone sensorinformation from the microphone of the first device, the first devicedetects the amplitude for each frequency band within the matched,pre-defined number of frequency bands selected (e.g., a finite number ofbands within a range of 20-22 kHz) and whichever band whose amplitudeexceeds a pre-defined threshold at some time t=y. Its center frequencyis selected as the dominant frequency and is assumed to be the emissionof the speaker of the second device. This frequency is then mapped, viathe pre-defined mapping, to a numerical value whose numerical value isselected as the current value of the sensor of the second device at thattime t=y. This value is used as the current, synchronized sensor valueof the sensor on the second device at that time t=y and is stored on thefirst device in memory with the sensor information being generated bysensors on the first device. It is important to note that there is nosignificance to time t=y or t=x. Also, it is important to note that awide range of varying frequencies can be selected in the human inaudiblerange.

Another method of synchronizing the time stamp between two devices isthe periodic electromagnetic radio frequency synchronization method.This method can be used between two wireless devices. In this method,the first device and the second device contain electromagnetic radios(e.g., a Bluetooth® 2.4 GHz electromagnetic radio). A wirelessconnection is established between the first and second device using theconnection protocol defined by the Bluetooth communication stack. Thesynchronization process occurs at the beginning of each measurementsession or at a sufficient interval to maintain a desired level ofsynchronicity between the two devices to avoid an undesirable level ofclock drift. The first device generates a first time stamp and stores itwithin a memory location within the embedded system of the first device.Simultaneously, a special request command—a special sequence of datathat has a pre-determined meaning—is sent from the first device to thesecond device wirelessly over the electromagnetic radio frequencycommunication connection established between the two electromagneticradios. The second device has been programmed to handle the receipt ofthe special request command. Upon receipt of the special requestcommand, the second device generates a second time stamp with itsinternal clock and immediately responds with a special response over theelectromagnetic radio frequency communication connection to the firstdevice. The special response from the second device to the first devicecontains the second time stamp generated by the second device. The firstdevice is programmed to handle the receipt of the special response fromthe second device. Once the special response from the second device isreceived, the first device stores the second time stamp, which wascontained within the special response, in its memory in a fashion thatassociates it with the first time stamp. A time delay is calculatedbetween the first time stamp and the second time stamp is calculated.When sensor information from the second device is aggregated with sensorinformation from the first device, the time delay is used to adjust thetime-alignment of sensor information that is collected from both thefirst device and second device.

In a preferred embodiment, these synchronization methods can be usedindependently from each other. In some embodiments, it is contemplatedthat a combination of two or more of those synchronization methods canbe used.

The sensor information in the form of a waveform can provide one or moredata feature at one or more data point. The data feature may comprise apoint on the waveform (e.g., an amplitude of a peak of the waveform, anamplitude of a foot of the waveform, etc.). The data feature maycomprise a time reference (a time at the peak of the waveform, a time atthe foot of the waveform, etc.) The time can be absolute time. In someembodiments, the time can be relative time.

From two or more data features of two or more sensor information, avalue of time delay can be derived. In a preferred embodiment, the timedelay is derived from a cross-correlation between the first data featureand the second data feature.

For example, as shown in FIG. 1, I-J of the BCG and W of the PPG or IPGare two data features from two different sensor information. The timedifference 110 between the max positive slope of I-J of the BCG to theonset of W of the PPG or IPG represents the time delay or pulse transittime that correlates to a diastolic pressure. Likewise, the timedifference 105 between the peak R of ECG to the onset W of PPGcorrelates with a systolic pressure.

Various values of time delays can be derived based on the data featuresand the type of signals. A Pulse Arrival Time (PAT) is the time delaybetween the time immediately after electrical systole of the heart andthe arrival of an arterial pressure wave to a distance away from theheart. It is contemplated that PAT comprises a time difference betweenECG and PPG signals, or a time difference between ECG and IPG signals.

Pulse Transit Time (PTT) is time delay between corresponding features oftwo cardiovascular waves where each wave relates to movement of bloodwithin the arterial tree and where each wave is measured at differentarterial distances from the heart and where each wave is measured withone of the following sensor information: PPG, IPG, BCG, and PCG. It iscontemplated that PTT_A comprises a time difference between PCG and PPG.Pulse Transit Time B (PTT_B) is time delay between the mechanical leftventricular contraction/blood ejection from the heart into the aorta andthe arrival of an arterial pressure wave to a distance away from theheart, or a time difference between BCG and PPG signals. It iscontemplated that Pulse Transit Time C (PTT_C) comprises a timedifference between two PPG signals.

PAT includes a delay known as the Pre-Ejection Period (PEP), which isthe time delay between electrical systolic of the ventricles of theheart and mechanical left ventricular contraction/blood ejection fromthe heart into the aorta. The PEP for any individual varies with everyheartbeat. Thus, Pulse Transit Time, which does not include the PEP, canprovide a more accurate tool to measure blood pressure.

The time delay derived based on two time references is correlated withthe blood pressure value. In some embodiments, it is contemplated thatthe blood pressure value and the time delay can be linearly correlatedas a function of P=Mt+N, where P is a systolic or diastolic bloodpressure, M and N are coefficients, t is a time delay (e.g., a pulsetransit time). In other embodiments, it is contemplated that the bloodpressure value and the time delay can be non-linearly correlated as afunction of P=Me^(−Nt), where P is a systolic or diastolic bloodpressure, M and N are coefficients, t is a time delay (e.g., a pulsetransit time). In some other embodiments, it is also contemplated thatthe blood pressure value and the time delay can be sigmoidallycorrelated.

A non-linear mapping of pulse transit time of cardiovascular time delayto Pulse Wave Velocity is based on the correlation among the velocity,time, and distance, as a function of v=d/t, where v is pulse wavevelocity, t is a time delay between two cardiovascular waves (e.g., apulse transit time), and d is the arterial distance. For example, thetime delay can be calculated based on the difference of two arterialdistances from the heart, where each arterial distance from the heart iscalculated by the distance from the heart to the location at which eachcardiovascular wave is captured.

The blood pressure value derived by the correlation function with thetime delay can be further adjusted based on various factors, such as anage, a gender, a height, a weight, an ethnicity, a BMI, an arm span, ahealth history, a health condition, a waist circumference, and anarterial distance between two physiological points of the person's body.

In a preferred embodiment, the blood pressure value of the personderived from the time delay can be provided to a user. The user can bethe person whose blood pressure is measured. However, it is alsocontemplated that the user can be a third party, including a healthcareprovider, a family member, an insurance provider, a personal trainer, orany other person or entities who are authorized to receive the person'shealth information.

In some embodiments, the user may receive the value of thecardiovascular time delay or one or more other metrics derived from thecardiovascular time delay. The metrics includes a life expectancy, acardiovascular health, and an arterial compliance, arterial elasticity,or distensibility, which are positively correlated with thecardiovascular time delay. The metric may also include an arterialstiffness, a cardiovascular risk, a risk of morbidity, or a risk ofmortality, which are negatively correlated with the cardiovascular timedelay.

Followings are various examples and embodiments to measure bloodpressures using one or more types of sensors in one or more mobile,wearable, or patch devices. It should be noted that any combinations ofdevices or sensors are contemplated in the present invention, and thepresent invention is not limited to the examples provided below.

EXAMPLES Example I: Measuring Blood Pressures Using a Microphone and aPhotodetector (PCG+PPG)

The mobile computational device is comprised of an embedded electricalsystem, power source, and product housing. The embedded electricalsystem is comprised of, but not limited to, an electrical hardwarecircuit consisting of a digital controller, analog-to-digitalconverters, a software uploaded to the digital controller responsiblefor driving the hardware components to accomplish the defined tasks(e.g., sensor functionality, sensor signal capture, etc.), at least oneacoustic-to-electrical converter (e.g., microphones), and at least onephotodetector or image sensor component. The photodetector or imagesensor component may include, but is not limited to, a semiconductorcharge-coupled devices (CCD), an active pixel sensors in complementarymetal-oxide-semiconductor (CMOS), or a N-type metal-oxide-semiconductor(NMOS, Live MOS) technologies. Herein either a photodetector or imagesensor will be referred to as a photodetector.

FIG. 4A shows a perspective view of the product housing for the mobilecomputational device 400. FIG. 4B shows a side view of the producthousing for the mobile computational device 410. The product housingconsists of an acoustic duct 420 and one or more embeddedacoustic-to-electrical converter components 425. At least one of theembedded acoustic-to-electrical converter components 425 are exposed toambient air via opening 405 of the acoustic duct 420 for proper captureof incident acoustic waves.

FIG. 4C shows a schematic view of measuring acoustic heart activity 430on the person's chest 450. To capture an acoustic heart acoustic wave460 transmitted from the heart 440, the user is specifically instructedto place the opening 405 of the acoustic duct 420 of the mobilecomputational device product housing 400 in direct skin contact with hisor her chest 450. To achieve improved capture of acoustical heartactivity signals and improved blood pressure measurement accuracy, theuser is further instructed to ensure that at least 50%, at least 70%, atleast 90% or the entire perimeter surface of the opening 405 of theacoustic duct 420 of the product housing remains in constant contactwith the skin of his or her chest 450. This instruction ensures a“skin-acoustic duct seal” that enables a confined column of air withinthe acoustic duct 420 to better propagate acoustical waves 460 generatedby the person's heart 440 inside the chest cavity and results inimproved conduction of such acoustical heart activity by theacoustic-to-electrical transducer of the mobile computational deviceembedded system.

At the same time the user is instructed to hold the acoustic duct of themobile computational device product housing in direct, sealed contactwith the person's chest, the user is also instructed to simultaneouslyplace the palmar tissue bed of one of his or her hand digits/phalanx ofthe left or right arm in direct contact with the photodetector housingof the same mobile computational device. This position that the usermust hold during a blood pressure measurement, which will be referred asthe measurement position, is held for the duration of the blood pressuremeasurement.

Every cardiac cycle of the person's heart produces analog, physiologicalbiosignals that include acoustic heart activity, arterial pressure waveactivity, and local skin tissue blood volume activity. The human heartis a four chamber heart comprising two ventricles and two atria with twoatrioventricular and two semilunar valves. Each atrioventricular valvefacilitates the passage of blood from one atrium into one ventricle.Each semilunar valve facilitates the passage of blood from one ventricleinto either the aorta or pulmonary artery. Within a single cardiac cycleblood fills each of the two atria, is then passed through eachatrioventricular valve into each respective ventricle, then passedthrough each semilunar valve into the aorta (from the left ventricle)and the pulmonary artery (from the right ventricle). The blood that isejected from the left ventricle of the heart into the aorta is thenpassed into either the left or right subclavian artery which feeds intothe brachial artery of that arm which subsequently feeds into the radialand ulnar arteries which both feed the palmar digital arteries of thehand digits of the respective arm. The blood within the palmar digitalarteries of each hand passes into the small microvasculature of thesubcutaneous and dermal tissue within the palmar tissue bed of eachdigit.

The acoustic heart activity trace captured in this method containsphysiological information about the occurrence of the closure of theatrioventricular and semilunar valves of the person's heart as well asphysiological information about the timing related to the ejection ofblood from the left ventricle of the heart into the aorta and peripheralarterial tree. During each cardiac cycle, the closure of both theatrioventricular and semilunar valves produce acoustic signals (acousticheart activity). Specifically, the near-synchronous closure of bothatrioventricular valves produce one predominant acoustic wave at onepoint in time (S1 acoustic wave) and the near-synchronous closure ofboth semilunar values produce a second predominant acoustic wave at alater point in time (S2 acoustic wave). The acoustic heart activity iscomprised of, but not limited to, the S1 and S2 acoustic waves. Theturbulent closure of heart valves causes acoustic perturbations that canbe detected with a proper acoustic transducer (e.g., a stethoscope).Signal peak detection and common bandpass signal processing techniquesare used to isolate the frequencies of interest in the acoustic heartactivity trace signal, particularly, but not limited to, those below1000 Hz, and used to identify the precise time reference associated withthe following information: left ventricular contraction/blood ejectionfrom the heart into the aorta for a single cardiac cycle, leftventricular ejection time (LVET), pre-ejection period (PEP), the openingand closing of the atrioventricular and semilunar valves.

During each cardiac cycle, blood that is ejected from the left ventricleinto the aorta produces an incident arterial blood pressure wave thatpropagates through the subclavian artery through the arterial arterythrough the radial and ulnar arteries through the palmar digitalarteries of the hand and into the small microvasculature of thesubcutaneous and dermal tissue within the palmar tissue bed of eachdigit of each hand. The propagating arterial pressure wave causeslocalized compression of and therefore localized increases to bloodvolume along its trajectory in the arterial tree. Human blood containsintrinsic biophysical properties in which it absorbs incident lightphotons. With each cardiac contraction an arterial pressure wave isgenerated and propagated along the arterial tree to the periphery of thecardiovascular system, reaching the microvasculature of the subcutaneousand dermal tissue of the skin. The propagating arterial pressure wavecauses localized compression of and therefore localized increases toblood volume along its trajectory in the arterial system. Because largervolumes of blood absorb larger amounts of incident light photons,changes in subcutaneous and dermal tissue blood volume are detectablewith the proper use of a photodetector aimed at or in direct contactwith the subcutaneous and dermal tissue bed.

In some embodiments, sampling of digitized outputs of the photodetectorand acoustic-to-electrical transducer may be conducted in a differentfrequency, and the sensor data may be updated asynchronously. Tosynchronously obtain sensor data from two different sensors, thesoftware running on the processor of the embedded system of the mobilecomputational device initiates a measurement session of which initiationis triggered by user interaction with the mobile computational device.The software allocates memory space within the embedded system either ona memory-equipped digital controller component or dedicated memorycomponent to hold in memory slots for 1) the most recent digital valueof the acoustic-to-electrical transducer, 2) the most recent digitalvalue of the photodetector, and 3) the session signal trace buffer.

The software activates the acoustic-to-electrical transducer. Incident,analog acoustic waves of the acoustic heart activity induce fluctuationsin outputted electrical activity of the acoustic-to-electricaltransducer. This electrical output is digitized via a dedicatedanalog-to-digital converter component, an analog-to-digital converterequipped digital controller component, or any hardware component withinthe embedded electrical system equipped with the ability to convert ananalog electrical signal into a discretely sampled digital signal.Updates of the digitized outputs of the acoustic-to-electricaltransducer, of which each update will be referred herein as the latestacoustic digital value, are routed into and handled by the softwarewhere a specific thread or loop of code is responsible for receiving thelatest acoustic digital values. The software activates the photodetectorand an available incident light source (e.g., a camera flash). Theincident light source either is also in direct contact with the palmartissue bed of the same digit or nearby. Periodic cardiac contractionslead to localized increases to blood volume at the person's palmartissue bed of the digit in contact with the photodetector. Theselocalized increases to blood volume cause more light to be absorbed andless light to be reflected back to the photodetector. Incident, analogfluctuations in reflected light from the palmar tissue bed of theperson's digit in contact with the photodetector induce eitherfluctuations in outputted electrical activity of the photodetector,which is subsequently digitized via a dedicated analog-to-digitalconverter component, an analog-to-digital converter equipped digitalcontroller component, or any hardware component within the embeddedelectrical system equipped with an analog to digital converter, orfluctuations in the individual color components (e.g., RGB components)of pixels from an image sensor type photodetector. Updates of thedigitized outputs of the photodetector, either in the form of framescomprised of pixels each pixel of which is comprised of a red, green,and blue component (for an image-type photodetector) or single-valueintensity values. The latest photodetector digital values are routedinto and handled by the software where a specific thread or loop of codeis responsible for receiving the latest photodetector digital values.

Every time the latest acoustic digital value is routed into and handledby the software, it is stored in memory as the most recent digital valueof the acoustic-to-electrical transducer. Every time the latestphotodetector digital value is routed into and handled by the software,it is stored in memory as the most recent digital value of thephotodetector.

In a synchronous periodic fashion, the software runs another thread orloop of code, which is responsible for grabbing the most recent digitalvalue of the acoustic-to-electrical transducer stored in memory and themost recent digital value of the photodetector stored in memory. At thesame time, the software generates a time stamp, as precise as possible,but ideally precise to one millisecond or less. The three values areappended to the session signal trace buffer in memory, generating asynchronized set of parallel physiological signal traces.

The Local Tissue Blood Volume Activity trace captured in this methodcontains physiological information about the pulsatile fluctuations ofblood volume present in the micro-vasculature and capillary beds of aregion of tissue on the surface of the body. The physiologicalinformation, represented as a plethysmogram, can be shown in a waveform.In the waveform, detection of a signal foot, a maximal slope, or a peakof the waveform can be used to identify the precise time referenceassociated with the arrival of an arterial pressure wave generated froma single cardiac cycle/left ventricular contraction of the heart.

Once the precise time references associated with the left ventricularcontraction of the heart and arterial pressure wave arrival at the localtissue region (e.g., the palmar tissue bed of the person's hand phalanx)are captured, the time delay associated with the subsequent arrival ofthe arterial pressure wave after the left ventricular contraction of theheart (the Pulse Transit Time A) is calculated by mathematical operationof subtraction between the two time references.

Once the Pulse Transit Time A is captured, a systolic blood pressure canbe measured based on a linear relationship between Pulse Transit Time Aand systolic blood pressure as a function of p=Mt+N, where p is asystolic blood pressure, t is a pulse transit time A (PTT_A) and M and Nare coefficients.

Once the Pulse Transit Time A is captured, a diastolic blood pressurecan be measured based on a linear relationship between Pulse TransitTime A and diastolic blood pressure as a function of p=Mt+N, where p isa diastolic blood pressure, t is a pulse transit time A (PTT_A) and Mand N are coefficients.

Example II: Measuring Blood Pressures Using an Accelerometer and aPhotodetector (BCG+PPG)

FIG. 5A shows an example of a method and system to measure bloodpressures using raw digital signal traces related to the mechanicalheart activity of the person 500, represented as BCG signals, and localtissue blood volume activity, represented as PPG signals. In a preferredembodiment, both signals can be captured by a single mobilecomputational device 505 equipped with an accelerometer and aphotodetector.

The mobile computational device 505 can be placed anywhere on the chest,preferably near the apex of the heart as a point of contact 520. It iscontemplated that any orientation of the mobile computational devicesufficiently coupled to the chest can capture the mechanical heartactivity from the accelerometer sensor. Orientations can include, but isnot limited to, pressing a side of the device 505 to the chest, pressingthe screen of the device to the chest, or pressing the back of thedevice 505 to the chest with sufficient physical coupling to capture themechanical heart activity. The person whose blood pressure is measuredcan be oriented in any position, including a sitting position, standing,or supine position. However, it is preferred that the vertical distance(measured along the gravitational force axis) between the person'slocation of PPG measurement 510 (e.g., a finger) and the fixed locationof the heart is zero during the duration of the measurement to ensurethe hydrostatic influences are minimized.

In other embodiments, raw digital signal traces related to themechanical heart activity of the person and local tissue blood volumeactivity of a person can be captured by a single wearable computationaldevice, which is equipped with an accelerometer 1135 and aphotodetector. FIG. 11A shows a schematic view 1100 of a person 1105measuring the blood pressure using a wearable device 1130. In thismethod and system, the person 1105 wears a wearable computational device1130 on the left or right arm, the wrist, forearm, or upper arm. Thewearable device 1130 is equipped with an accelerometer and one or morephotoemitter and one or more photodetector components collectivelyforming a PPG Sensor 1110. The PPG Sensor 1110 is built into the producthousing of the wearable device 1130. The PPG Sensor 1110 is in directcontact with the person's skin of the arm at a point of contact A 1125,and maintains constant contact with the skin. While still being worn onthe arm of the person 1105, the wearable device 1130 is put into contactwith the chest of the person at a point of contact B 1115. The wearabledevice 1130 can be placed anywhere on the chest of the person 1105, butwith ideal placement near the apex of the heart. Any orientation of thewearable device sufficiently coupled to the chest to capture themechanical heart activity from the accelerometer sensor is sufficient.

The person whose blood pressure is measured can be oriented in anypositions, including a sitting position, standing position, or supineposition. However, it is preferred that the vertical distance (measuredalong the gravitational force axis) between the person's location of PPGmeasurement 1125 (e.g., the wrist) and the fixed location of the heartis zero during the duration of the measurement to ensure the hydrostaticinfluences are minimized.

The physiological action of the heart of the person produces heart andlocal tissue displacement detected by the wearable device accelerometer1135, which detects the real-time transient changes in the person's BCGsignal. BCG signals provide information of the time, at which each heartcontraction occurs and the force of each heart contraction.Simultaneously, the PPG Sensor 1110 measures the real-time transientchanges in blood flow at the point of contact A 1125 that provideinformation of the time of each pulse arrival produced by eachcontraction of the person's heart.

FIGS. 5B and 11B show schematic diagrams to process BCG signals and PPGsignals in two different embodiments, respectively. The mechanical heartactivity and the local tissue blood volume activity of a person arecaptured and data features (e.g., time reference) are derived from atleast one or more data points as described above. Once the precise timereference associated with the mechanical systole or ventricular cardiaccontraction event is selected as the time reference for the leftventricular contraction event/time of blood ejection from the heart andtime reference associated with the arterial pressure wave arrival at thelocal tissue region (e.g., the palmar tissue bed of the person's handphalanx) are both captured, the time delay associated with thesubsequent arrival of the arterial pressure wave after the leftventricular contraction of the heart (the Pulse Transit Time B) iscalculated by mathematical operation of subtraction between the two timereferences. The Pulse Transit Time B does not include the delay known asthe Pre-Ejection Period, which is the time delay between electricalsystolic of the ventricles of the heart and mechanical left ventricularcontraction/blood ejection from the heart into the aorta. Because ofthis, using the Pulse Transit Time B can more accurately measure bloodpressures.

Once the Pulse Transit Time B is captured, a systolic blood pressure canbe measured based on a linear relationship between Pulse Transit Time Band systolic blood pressure as a function of p=Mt+N, where p is asystolic blood pressure, t is a pulse transit time B (PTT_B) and M and Nare coefficients.

Once the Pulse Transit Time B is captured, a diastolic blood pressurecan be measured based on a linear relationship between Pulse TransitTime B and diastolic blood pressure as a function of p=Mt+N, where p isa diastolic blood pressure, t is a pulse transit time B (PTT_B) and Mand N are coefficients.

Example III: Measuring Blood Pressures Using an Accelerometer and aMicrophone (BCG+PCG)

The combination of using an accelerometer and a microphone to detect BCGsignal and PCG signal, respectively, would provide more informationabout the cardiac cycle. Capturing PCG signals using a microphoneprovides information of the total time period in which blood is ejectingfrom the left ventricle during each cardiac cycle and information of thetotal time period in which blood is not ejecting from the left ventricleduring each cardiac cycle. However, PCG signals may not provide theprecise moment in time, in which blood ejection from the left ventricleinto the aorta begins, but an approximation of it from the time of S1.PCG signals do provide the precise moment in time in which bloodejection from the left ventricle into the aorta ends (beginning of theS2 component of closure of the aortic semilunar valve). BCG signalscaptured by the accelerometer can provide information of the moment ofmaximum ventricular contraction, which is associated with a point intime within the time period of blood ejection from the left ventricleinto the aorta. Therefore, combination of PCG data with BCG data canprovide a new approximate parameter that aids with a more accurate bloodpressure calculation. Such new parameters include the time periodbetween 1) the beginning of blood ejection from the left ventricle intothe aorta, 2) the time of maximum blood ejection from the left ventricleinto the aorta, which is the time that corresponds with maximummechanical activity detected by the BCG and 3) the ending of bloodejection from the left ventricle into the aorta.

Example IV: Measuring Blood Pressures Using at Least Two Photodetectors(PPG+PPG)

FIG. 6A shows an example of a method and system to measure bloodpressures using raw digital signal traces related to the local tissueblood volume activity, represented as PPG signals of the person 600. Inthis method and system, a single mobile computational device 605equipped with at least two photodetectors 610, 630 is used to capturePPG signals at least in two different parts of the person's body.

The user is instructed to aim a first photodetector (e.g., a camera lensof a mobile computational device 605) at, but not limited to thelocation of the person's face. Ambient incident photons interact withthe blood-perfused skin tissue bed of the person at his or her face andare reflected along a path 640 and captured by the first photodetector630 of mobile computational device 605. The time of arrival of acardiovascular pulse wave at the face produced by each contraction ofthe person's heart is detected. Concurrently, the user is instructed tocover a second photodetector 610 and the device's flash LED with theperson's hand digit/phalanx palmar tissue bed region. The secondphotodetector detects the time of the arrival of a cardiovascular pulsewave at the person's digit/phalanx palmar tissue bed region produced byeach contraction of the person's heart.

In a preferred embodiment, the first location for capturing the localtissue blood volume activity of the person is preferably located at adifferent cardiovascular distance from the heart than the secondlocation for capturing the local tissue blood volume activity of theperson. For example, the first location of capturing local tissue bloodvolume activity with a first photodetector 630 may be a portion of theface 620 of the person (e.g., the forehead, the cheeks under the eyes,the entire face, the chin, etc.). The skin tissue bed of the person'swrist, arm, or finger can be used as the second location of contact withthe second photodetector 610 of the mobile device 605 to capture thelocal tissue blood volume activity. However, it is contemplated thatother parts of the body can be used as a second location of contact.

In other embodiments, raw digital signal traces related to the localtissue blood volume activity of a person can be captured by one or morewearable devices to continuously measure blood pressure as the persongoes about their day without the need for the user to stop what they aredoing to take a measurement. In this method and system shown in FIG. 7A,at least two computational wireless devices 720, 730 are used to capturethe local tissue blood volume activity. Each of wireless devices is awearable device with one or more photodetectors 710, 740.

The first photodetector 710 contacts the skin tissue bed of the person'swrist, arm, or finger as the location of contact for the wearable deviceresponsible for capturing the local tissue blood volume activity.However, other part of the body can be used such as the person's foot(e.g., with a wearable sock with embedded sensor). The secondphotodetector 740 contacts the skin of the portion of the person's body,which has different distance from the heart from the first sensorcapturing the local tissue blood volume activity. In a preferredembodiment, these two wearable devices could both be patches. However,it is also contemplated that one device is a patch and the other deviceis another type of wearable devices (e.g. a fitness tracker, awristband, a smart watch, etc.).

FIGS. 6B and 7B show schematic diagrams to process two PPG signals intwo different embodiments, respectively. The signals for local tissueblood volume activity of a person are captured and data features (e.g.,time reference) are derived from at least one or more data points asdescribed above. Once the precise, first time reference associated withthe first arterial pressure wave arrival at the local tissue region ofinterest of the first sensor (e.g., tissue bed of the person's hand,finger, arm, leg, torso) and the second time reference associated withthe first arterial pressure wave arrival at the local tissue region ofinterest of the second sensor (e.g., the tissue bed of the person'sface) are both captured, the time delay associated with the subsequentarrival of the arterial pressure wave (the Pulse Transit Time C) iscalculated by mathematical operation of subtraction between the two timereferences.

Once the Pulse Transit Time C is captured, a systolic blood pressure canbe measured based on a linear relationship between Pulse Transit Time Cand systolic blood pressure as a function of p=Mt+N, where p is asystolic blood pressure, t is a pulse transit time C (PTT_C) and M and Nare coefficients.

Once the Pulse Transit Time C is captured, a diastolic blood pressurecan be measured based on a linear relationship between Pulse TransitTime C and diastolic blood pressure as a function of p=Mt+N, where p isa diastolic blood pressure, t is a pulse transit time C (PTT_C) and Mand N are coefficients.

Example V: Measuring Blood Pressures Using an Array of Electrodes and aPhotodetector (ECG+PPG)

FIG. 8A-B shows an example of a method and system to measure bloodpressures using raw digital signal traces related to the electricalheart activity of the person 800, represented as ECG signals, and localtissue blood volume activity, represented as PPG signals. In a preferredembodiment, both signals can be captured by one mobile device 810 with aphotodetector 805 as shown in FIG. 8A, and a wearable device 820 with anarray of electrode 830 as shown in FIG. 8B. It is contemplated that bothdevices are configured to facilitate wireless communication. The dataflow of the two devices is facilitated in the following fashion: thewearable device communicates electrical heart activity signal trace datavia wireless communication to the mobile computational device with thephotodetector, where the two signals are synchronized in time. Wirelesscommunication may be carried out via, but by no means limited to,short-range electromagnetic radio frequency communication using thefrequency band of 2.4 GHz, in which case both devices are equipped with2.4 GHz electromagnetic radios. An alternative means of wirelesscommunication that could be employed involves the wearable device withthe electrode array being equipped with an electrical-to-acoustictransducer (e.g., a speaker) capable of producing inaudiblehigh-frequency sounds whose instantaneous sound frequency emissions varyin direct proportion to the instantaneous values of the electrical heartactivity. Such inaudible sounds are detected by anacoustic-to-electrical transducer (e.g., a microphone) on the mobilecomputational device with the photodetector.

In the method and system shown in FIG. 8, the wearable electrical heartsensor is placed on the chest or back for proper trans-thoracic captureof the electrical activity of the heart, which are locations capable ofproviding an adequately strong signal to noise ratio for the capture ofthe electrical heart activity trace of the person. However, it is alsocontemplated that the wearable device can be placed on the lower body,including the abdomen or lower back, or the upper portion of the body,including the neck or behind the ear.

In other embodiment, as shown in FIG. 9A, ECG signals and PPG signalscan be captured by two wearable devices 910, 930 to continuously measureblood pressure as the person 900 goes about their day without the needfor the user to stop what they are doing to take a measurement. In thismethod and system shown in FIG. 9, the first wearable device 910 has anarray of electrode 920, which can capture ECG signals from the person'sheart activity. The second wearable device 930 contacts the skin tissuebed of the person's wrist, arm, or finger as the location of contact forthe wearable device responsible for capturing the local tissue bloodvolume activity. However, other part of the body can be used such as theperson's foot (e.g., with a wearable sock with an embedded sensor). Thefirst wearable device 910 can be placed on the chest or back of theperson 900 for proper transthoracic capture of the electrical activityof the heart. However, it is also contemplated that the wearable device910 can be placed on the lower body, including the abdomen or lowerback, or the upper portion of the body, including the neck or behind theear.

In some other embodiments, as shown in FIG. 10A, only one wearabledevice 1010 can be used to capture both ECG and PPG signals from theperson's heart activity. In this method and system, the device isequipped with an electrode array with an array of at least twoelectrodes (ECG sensor) and a photodetector (PPG sensor). In this methodand system, ECG sensors 1030 may contact the skin tissue bed of theperson's wrist, arm, or finger 1005, 1020, 1025. The ECG sensors 1030may also contact the skin of the chest or back of the person 1000.However, it is also contemplated that the wearable device can be placedon the lower body, including the abdomen or lower back, or the upperportion of the body, including the neck or behind the ear. The PPGsensors 1015 may contact the skin tissue bed of the person's wrist, arm,or finger 1005, 1020, 1025. However, other part of the body can be usedsuch as the person's foot (e.g., with a wearable sock with embeddedsensor).

In some other embodiments, as shown in FIG. 12A, only one mobile device1200 may be used to capture both ECG and PPG signals from the person'sheart activity. In this method and system, the device 1200 is equippedwith an electrode array with an array of at least two electrode contacts(ECG sensor) 1215, 1220. The device 1200 is also equipped with one ormore photoemitters 1225 and one or more photodetector components 1230,which may include, but is not limited to, a Camera flash LED and Cameralens, collectively forming a PPG Sensor. The front view 1205 of themobile device 1200 shows a first electrode 1215. The rear view 1210 ofthe mobile device 1200 shows a photodetector 1230, photoemitter 1225 anda second electrode contact 1220.

In this method and system, two electrode contacts 1215, 1220 are capableof measuring an electrical potential drop across the two electrodecontacts 1215, 1220 through their interconnected circuitry. The user isinstructed to place the skin of one hand 1235 in direct contact withelectrode contact A 1215 and the skin of the opposing hand 1240 indirect contact with electrode contact B 1220 forming the “ECG Sensor.The user is also instructed to place the hand digit/phalanx palmartissue bed region 1 of one of the hands over the PPG Sensor components.The real-time transient changes in electrical potential across electrodecontact A and electrode contact B form a continuous quantification ofthe electrical activity of the person's heart (ECG signals) and amongother heart-based physiological parameters, the ECG signal is used todetect the time at which each heart contraction occurs. Simultaneously,the PPG Sensor measures the real-time transient changes in blood flow atthe point of contact 1245 of the opposing hand 1240. Together, theperson's ECG and the person's PPG enable the derivation of acardiovascular time delay, which is used to produce a measure of bloodpressure.

FIGS. 8C, 9B, 10B, and 12B show schematic diagrams to process ECG signaland PPG signal in three different embodiments, respectively. The signalsfor a person's heart's electrical activity and local tissue blood volumeactivity of the person are captured, and data features (e.g., timereference) are derived from at least one or more data points asdescribed above. Once the precise time reference associated with theelectrical systole (and subsequent left ventricular contraction of theheart) and time reference associated with the arterial pressure wavearrival at the local tissue region of interest (e.g., the palmar tissuebed of the person's hand digit/phalanx) are both captured, the timedelay associated with the subsequent arrival of the arterial pressurewave after the electrical systolic (the Pulse Arrival Time) iscalculated by mathematical operation of subtraction between the two timereferences. The Pulse Arrival Time includes a delay known as thePre-Ejection Period, which is the time delay between electrical systolicof the ventricles of the heart and mechanical left ventricularcontraction/blood ejection from the heart into the aorta.

Once the Pulse Arrival Time is captured, a systolic blood pressure canbe measured based on a linear relationship between Pulse Arrival Timeand systolic blood pressure as a function of p=Mt+N, where p is asystolic blood pressure, t is a pulse arrival time (PAT) and M and N arecoefficients.

Once the Pulse Arrival Time is captured, a diastolic blood pressure canbe measured based on a linear relationship between Pulse Arrival Timeand diastolic blood pressure as a function of p=Mt+N, where p is adiastolic blood pressure, t is a pulse arrival time (PT) and M and N arecoefficients.

Example VI: Measuring Blood Pressures Using an Array of Electrodes andan Accelerometer (ECG+BCG)

There is a time delay between the time of peak electrical depolarizationof the ventricles and the time of peak mechanical contraction of theventricles referred to as the Pre-Ejection Period (PEP). The combinationof BCG signal and ECG signal provides information of an indication ofthe pre-ejection period between electrical systole and mechanicalsystole of the heart. Furthermore, it provides an easy way to capturePEP (time between peak electrical depolarization of the ventricles andpeak mechanical contraction of the ventricles), which correlates withcontraction force of the heart. Contraction force of the heartcorrelates with systolic blood pressure (as systolic blood pressure is apressure that results both from arterial vascular activity as well asheart/ventricular activity). Thus, this PEP value can be used as anadditional piece of information to improve the accuracy of bloodpressure measurement calculations.

Example VII: Measuring Blood Pressures Using Three Types of SensorInformation: A Combination of Three of the Following: ECG, EEG, PPG,PCG, and IPG

In some embodiments, at least three types of sensors or sensorinformation may be used together to derive blood pressure of the person.Three types of sensors may be placed in one mobile or wearable device.It is also contemplated that two sensors are placed in one mobile orwearable device, and the other sensor is placed in another mobile orwearable device. It is also contemplated that three types of sensors areplaced in three distinct mobile or wearable devices.

In these embodiments, a software configured to obtain a first sensorinformation from a first sensor, a second sensor information from asecond sensor, and a third sensor information from a third sensor nearsimultaneously. The first sensor information comprises a first datapoint, the second sensor information comprises a second data point, andthe third sensor information comprises a third data point. Based on thefirst, second, and third data points, first data feature, second datafeature, and the third data feature can be derived, respectively.

As described above, ECG is used to capture a time reference, which ismostly by measuring the time associated with the R-peak, related to theelectrical systole/depolarization event of a single cardiac cycle. BCGis used to capture a time reference relating to the positive or negativemaximum slopes, a peak, or a foot of the BCG waveform related to themechanical systole event of a single cardiac cycle. PPG is used tocapture a time reference relating to the a foot, a maximum slope, or apeak of an incident PPG waveform related to the arrival of an arterialpulse pressure wave at a tissue region of interest some arterialdistance away from the heart. IPG is used to capture a time referencerelating to a foot, a maximum slope, or a peak of an incident IPGwaveform related to the arrival of an arterial pulse pressure wave at atissue region of interest some arterial distance away from the heart.PCG is used to capture a time reference relating to the mechanicalsystole event of a single cardiac cycle by detecting the S1 heart sound.

Combination of ECG, BCG, and PPG

Pre-ejection period (PEP) is a time delay between electrical systole andmechanical systole of the heart. Use of ECG-PPG dual sensor methods tocapture a cardiovascular time delay may introduce errors in such a timedelay because it includes the PEP, which varies independent of bloodpressure along the arterial tree. By employing three sensors, ECG, BCG,PPG to derive the value of blood pressure, accuracy in blood pressuremeasurement can be improved because the BCG sensor information andderived time reference associated with mechanical systole of the heartcan be used to identify the PEP for each cardiac cycle of the heart.

Combination of ECG, BCG, and IPG

Pre-ejection period (PEP) is a time delay between electrical systole andmechanical systole of the heart. Use of ECG-IPG dual sensor methods tocapture a cardiovascular time delay may introduce errors in such a timedelay because it includes the PEP, which varies independent of bloodpressure along the arterial tree. By employing three sensors, ECG, BCG,and IPG to derive blood pressure, accuracy in blood pressure measurementcan be improved because the BCG sensor information and derived timereference associated with mechanical systole of the heart can be used toidentify the PEP for each cardiac cycle of the heart.

Combination of ECG, PCG, and PPG

S1 event in PCG corresponds to the mechanical systole of the heart.Hence, the PCG is used to identify in this method the mechanical systoleof the heart by capturing the S1 sound. Pre-ejection period (PEP) is atime delay between electrical systole and mechanical systole of theheart. Use of ECG-PPG dual sensor methods alone to capture acardiovascular time delay that correlates to blood pressure can besubject to a rather significant error. This potential error is caused bythe PEP, which is included in the cardiovascular time delay. By adding aPCG sensor to two sensors, ECG and PPG, to measure blood pressure,accuracy in blood pressure measurement can be improved because the PCGsensor information and derived time reference associated with mechanicalsystole of the heart can be used to identify and eliminate the PEP foreach cardiac cycle of the heart from the cardiovascular time delay usedto measure blood pressure.

Combination of ECG, PCG, and IPG

S1 event in PCG corresponds to the mechanical systole of the heart.Hence, the PCG is used to identify in this method the mechanical systoleof the heart by capturing the S1 sound. Pre-ejection period (PEP) is atime delay between electrical systole and mechanical systole of theheart. Use of ECG-PPG dual sensor methods alone to capture acardiovascular time delay that correlates to blood pressure can besubject to a rather significant error. This potential error is caused bythe PEP, which is included in the cardiovascular time delay. By adding aPCG sensor to two sensors, ECG and IPG, method of measuring bloodpressure, accuracy in blood pressure measurement can be improved becausethe PCG sensor information and derived time reference associated withmechanical systole of the heart can be used to identify and eliminatethe PEP for each cardiac cycle of the heart from the cardiovascular timedelay used to measure blood pressure.

Combination of BCG, PCG, and PPG

In this method, PCG is used to capture the left ventricular ejectiontime (LVET) by identifying the delay between a time reference within theS1 heart sound and a time reference within the S2 heart sound of thesame cardiac cycle. Thus, PCG can be used to improve the accuracy of thesystolic blood pressure measurement because LVET is captured in additionto the cardiovascular time delay already captured that correlates withboth systolic and diastolic blood pressure that is calculated by a delayassociated with a point in the BCG wave and a point within the PPG wave.The value of LVET is used to adjust the coefficients in the relationshipthat is used to derive BP from PTT (e.g., in a linear fashion: the M andN coefficients in a function of p=Mt+N).

Sensor information of ECG, BCG, PPG, PCG or IPG can be obtained and datafeatures from each sensor information on each data point are derived asdescribed above. Once data features are derived, one or more time delaysare derived based on the correlation among the three data features. In apreferred embodiment, the time delay is derived from a cross-correlationbetween the first data feature and the second data feature. For example,a first time delay can be derived based on the first data feature andthe second data feature, a second time delay based on the first datafeature and the third data feature, and a third time delay based on thesecond data feature and the third data feature.

The time delay derived based on three time references is correlated withthe blood pressure value. In some embodiments, it is contemplated thatthe blood pressure value and the time delay can be linearly correlatedas a function of P=Mt+N, where P is a systolic or diastolic bloodpressure, M and N are coefficients, t is a time delay (e.g., pulsetransit time). In other embodiments, it is contemplated that the bloodpressure value and the time delay can be non-linearly correlated as afunction of P=Me^(−Nt), where P is a systolic or diastolic bloodpressure, M and N are coefficients, t is a time delay (e.g., pulsetransit time). In some other embodiments, it is also contemplated thatthe blood pressure value and the time delay can be sigmoidallycorrelated. It is preferred that at least two of three time delays arecorrelated to a blood pressure value of the person. However, it is alsocontemplated that only one of three time delays is correlated to a bloodpressure value of the person.

The blood pressure value derived by the correlation function with thetime delay can be further adjusted based on various factors, such as anage, a gender, a height, a weight, an ethnicity, a BMI, an arm span, ahealth history, a health condition, a waist circumference, and anarterial distance between two physiological points of the person's body.

The derived blood pressure value can be provided to a user. The user canbe the person whose blood pressure is measured. However, it is alsocontemplated that the user can be a third party, including a healthcareprovider, a family member, an insurance provider, a personal trainer, orany other person or entities who are authorized to receive person'shealth information.

It should be apparent to those skilled in the art that many moremodifications besides those already described are possible withoutdeparting from the inventive concepts herein. The inventive subjectmatter, therefore, is not to be restricted except in the spirit of theappended claims. Moreover, in interpreting both the specification andthe claims, all terms should be interpreted in the broadest possiblemanner consistent with the context. In particular, the terms “comprises”and “comprising” should be interpreted as referring to elements,components, or steps in a non-exclusive manner, indicating that thereferenced elements, components, or steps may be present, or utilized,or combined with other elements, components, or steps that are notexpressly referenced. Where the specification claims refers to at leastone of something selected from the group consisting of A, B, C . . . andN, the text should be interpreted as requiring only one element from thegroup, not A plus N, or B plus N, etc.

What is claimed is:
 1. A method of measuring blood pressure of a person,comprising: obtaining a first cardiac waveform from an accelerometer, asecond waveform from a photodetector, and a third waveform from amicrophone near simultaneously, at a hand-held mobile device comprisingthe accelerometer, the microphone, and the photodetector, wherein: thefirst cardiac waveform is obtained near the heart of the person using atleast one axis of acceleration from the accelerometer, where the atleast one axis of acceleration is selected based on the position of thehand-held mobile device relative to the coronal plane of the person; andthe second waveform is obtained at a finger of the person held near theheart of the person; deriving, at one or more processors communicativelycoupled to the device, a first data feature based on the first cardiacwaveform, a second data feature based on the second waveform, and athird data feature based on the third waveform; deriving, at the one ormore processors, two time delays based on the first data feature, thesecond data feature, and the third data feature, wherein: each of thetwo time delays is derived based on two of: the first data feature, thesecond data feature, and the third data feature; deriving, at the one ormore processors, a blood pressure measurement of the person based on thetwo time delays, the blood pressure measurement comprising a systolicblood pressure value and a diastolic blood pressure value; and providinga user the blood pressure measurement of the person.
 2. The method ofclaim 1, wherein the first data feature comprises one of the following:a peak of the first cardiac waveform, a foot of the first cardiacwaveform, a point of maximum slope of the first cardiac waveform, apoint of minimum slope of the first cardiac waveform, a time to peak ofthe first cardiac waveform, a width of a peak, a peak of the first orsecond derivative of the first cardiac waveform, a foot of the first orsecond derivative of the first cardiac waveform, a point of maximumslope of the first or second derivative of the first cardiac waveform,and a point of minimum slope of the first or second derivative of thefirst cardiac waveform.
 3. The method of claim 1, wherein the firstcardiac waveform is obtained near the heart of the person using only oneaxis of acceleration from the accelerometer.
 4. The method of claim 1,further comprising the step of synchronizing the first cardiac waveformand the second waveform with a time stamp.
 5. The method of claim 1,wherein one of the two time delays is derived from a cross-correlationbetween the first data feature and the second data feature.
 6. Themethod of claim 1, further comprising a step of adjusting the bloodpressure measurement based on at least one of the following: an age, agender, a height, a weight, an ethnicity, a BMI, an arm span, a healthhistory, a health condition, a waist circumference, and an arterialdistance between two physiological points of the person's body using theone or more processors.
 7. A blood pressure monitoring system formeasuring blood pressure of a person, comprising: a hand-held mobiledevice comprising a housing, an accelerometer, a photodetector, amicrophone, and one or more processors communicatively coupled to thedevice and configured to execute a software stored on a non-transientcomputer-readable memory, wherein the software is configured to:activate the accelerometer and obtain a first cardiac waveform from theaccelerometer near the heart of the person using at least one axis ofacceleration from the accelerometer, where the at least one axis ofacceleration is selected based on the position of the hand-held mobiledevice relative to the coronal plane of the person; activate thephotodetector and obtain a second waveform at a finger of the personheld near the heart of the person; activate the microphone and obtain athird waveform from the microphone; synchronize the first cardiacwaveform, the second waveform, and the third waveform by obtaining thefirst cardiac waveform, the second waveform, and the third waveform nearsimultaneously, wherein the first cardiac waveform comprises a firstdata feature, the second waveform comprises a second data feature, andthe third waveform comprises a third data feature; derive, at the one ormore processors, a first time reference based on the first data feature;derive, at the one or more processors, a second time reference based onthe second data feature; derive, at the one or more processors, a thirdtime reference based on the third data feature; derive, at the one ormore processors, two time delays based on the first, second, and thirdtime references, wherein: each of the two time delays is derived basedon two of: the first time reference, the second time reference, and thethird time reference; derive, at the one or more processors, a bloodpressure measurement of the person based on the two time delays, theblood pressure measurement comprising a systolic blood pressure valueand a diastolic blood pressure value; and provide a user the bloodpressure measurement of the person.
 8. The system of claim 7, whereinthe first data feature comprises one of the following: a peak of thefirst cardiac waveform, a foot of the first cardiac waveform, and apoint of maximum slope of the first cardiac waveform, a point of minimumslope of the first cardiac waveform, a time to peak of the first cardiacwaveform, a width of a peak, a peak of the first or second derivative ofthe first cardiac waveform, a foot of the first or second derivative ofthe first cardiac waveform, a point of maximum slope of the first orsecond derivative of the first cardiac waveform, and a point of minimumslope of the first or second derivative of the first cardiac waveform.9. The system of claim 7, wherein the first cardiac waveform is obtainednear the heart of the person using only one axis of acceleration fromthe accelerometer.
 10. The system of claim 7, wherein the software isfurther configured to synchronize the first cardiac waveform and thesecond waveform with a time stamp.
 11. The system of claim 7, whereinone of the two time delays is derived from a cross-correlation betweenthe first data feature and the second data feature.
 12. The system ofclaim 7, wherein the software is further configured to adjust the bloodpressure measurement based on at least one of the following: an age, agender, a height, a weight, an ethnicity, a BMI, an arm span, a healthhistory, a health condition, a waist circumference, and an arterialdistance between two physiological points of the person's body.
 13. Amethod of measuring a cardiovascular time delay of a person, comprising:obtaining a first cardiac waveform from an accelerometer, a secondwaveform from a photodetector, and a third waveform from a microphonenear simultaneously, at a hand-held mobile device comprising theaccelerometer, the microphone, and the photodetector; wherein the firstcardiac waveform is obtained near the heart of the person using at leastone axis of acceleration from the accelerometer, where the at least oneaxis of acceleration is selected based on the position of the hand-heldmobile device relative to the coronal plane of the person; wherein thesecond waveform is obtained at a finger of the person held near theheart of the person; wherein the third waveform, a cardiac waveform, isobtained near the heart of the person; deriving, at one or moreprocessors communicatively coupled to the device, a first data featurebased on the first cardiac waveform, a second data feature based on thesecond waveform, and a third data feature based on the third waveform;deriving, at the one or more processors, a cardiovascular time delay anda second time delay based on the first data feature, the second datafeature, and the third data feature, wherein the cardiovascular timedelay and the second time delay are each derived based on two of: thefirst data feature, the second data feature, and the third data feature;adjusting the cardiovascular time delay based on the second time delay;and providing a user at least one of the following: the adjustedcardiovascular time delay and a metric derived from the adjustedcardiovascular time delay of the person.
 14. The method of claim 13,wherein the first data feature comprises one of the following: a peak ofthe first cardiac waveform, a foot of the first cardiac waveform, and apoint of maximum slope of the first cardiac waveform, a point of minimumslope of the first cardiac waveform, a time to peak of the first cardiacwaveform, a width of a peak, a peak of the first or second derivative ofthe first cardiac waveform, a foot of the first or second derivative ofthe first cardiac waveform, a point of maximum slope of the first orsecond derivative of the first cardiac waveform, and a point of minimumslope of the first or second derivative of the first cardiac waveform.15. The method of claim 13, wherein the first cardiac waveform isobtained near the heart of the person using only one axis ofacceleration from the accelerometer.
 16. The method of claim 13, furthercomprising the step of synchronizing the first, second and thirdwaveforms with a time stamp.
 17. The method of claim 13, wherein thethird waveform is obtained by placing the microphone on the chest of theperson.
 18. The method of claim 13, wherein the cardiovascular timedelay is derived from a cross-correlation between the first data featureand the second data feature.
 19. The method of claim 13, wherein themetric derived from the cardiovascular time delay includes at least oneof the following: a blood pressure, a pulse transit time, a pulse wavevelocity, a pulse arrival time, a life expectancy, a cardiovascularhealth, a cardiovascular fitness level, an arterial compliance, anarterial distensibility, an arterial elasticity, an arterial stiffness,a cardiovascular risk, risk of morbidity, and a risk of mortality.